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Background: Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown. Methods: A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF. Results: The overall 10-year risk of AF was 0.67% (95% CI: 0.61–0.73%) for index age 45 years, 2.05% (95% CI: 1.96–2.13%) for index age 55 years, and 6.34% (95% CI: 6.21–6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS. Conclusions: Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions. [ABSTRACT FROM AUTHOR]

Background. Ischaemia with nonobstructive coronary arteries is most commonly caused by coronary microvascular dysfunction but remains difficult to diagnose without invasive testing. Myocardial blood flow (MBF) can be quantified noninvasively on stress perfusion cardiac magnetic resonance (CMR) or positron emission tomography but neither is routinely used in clinical practice due to practical and technical constraints. Quantification of coronary sinus (CS) flow may represent a simpler method for CMR MBF quantification. 4D flow CMR offers comprehensive intracardiac and transvalvular flow quantification. However, it is feasibility to quantify MBF remains unknown. Methods. Patients with acute myocardial infarction (MI) and healthy volunteers underwent CMR. The CS contours were traced from the 2-chamber view. A reformatted phase contrast plane was generated through the CS, and flow was quantified using 4D flow CMR over the cardiac cycle and normalised for myocardial mass. MBF and resistance (MyoR) was determined in ten healthy volunteers, ten patients with myocardial infarction (MI) without microvascular obstruction (MVO), and ten with known MVO. Results. MBF was quantified in all 30 subjects. MBF was highest in healthy controls (123.8 ± 48.4 mL/min), significantly lower in those with MI (85.7 ± 30.5 mL/min), and even lower in those with MI and MVO (67.9 ± 29.2 mL/min/) (P < 0.01 for both differences). Compared with healthy controls, MyoR was higher in those with MI and even higher in those with MI and MVO (0.79 (±0.35) versus 1.10 (±0.50) versus 1.50 (±0.69), P = 0.02). Conclusions. MBF and MyoR can be quantified from 4D flow CMR. Resting MBF was reduced in patients with MI and MVO. [ABSTRACT FROM AUTHOR]

We wanted to assess if "Explainable AI" in the form of extreme gradient boosting (XGBoost) could outperform traditional logistic regression in predicting myocardial infarction (MI) in a large cohort. Two machine learning methods, XGBoost and logistic regression, were compared in predicting risk of MI. The UK Biobank is a population-based prospective cohort including 502 506 volunteers with active consent, aged 40 to 69 years at recruitment from 2006 to 2010. These subjects were followed until end of 2019 and the primary outcome was myocardial infarction. Both models were trained using 90% of the cohort. The remaining 10% was used as a test set. Both models were equally precise, but the regression model classified more of the healthy class correctly. XGBoost was more accurate in identifying individuals who later suffered a myocardial infarction. Receiver operator characteristic (ROC) scores are class size invariant. In this metric XGBoost outperformed the logistic regression model, with ROC scores of 0.86 (accuracy 0.75 (CI ±0.00379) and 0.77 (accuracy 0.77 (CI ± 0.00369) respectively. Secondly, we demonstrate how SHAPley values can be used to visualize and interpret the predictions made by XGBoost models, both for the cohort test set and for individuals. The XGBoost machine learning model shows very promising results in evaluating risk of MI in a large and diverse population. This model can be used, and visualized, both for individual assessments and in larger cohorts. The predictions made by the XGBoost models, points toward a future where "Explainable AI" may help to bridge the gap between medicine and data science. [ABSTRACT FROM AUTHOR]

We wanted to assess if "Explainable AI" in the form of extreme gradient boosting (XGBoost) could outperform traditional logistic regression in predicting myocardial infarction (MI) in a large cohort. Two machine learning methods, XGBoost and logistic regression, were compared in predicting risk of MI. The UK Biobank is a population-based prospective cohort including 502 506 volunteers with active consent, aged 40 to 69 years at recruitment from 2006 to 2010. These subjects were followed until end of 2019 and the primary outcome was myocardial infarction. Both models were trained using 90% of the cohort. The remaining 10% was used as a test set. Both models were equally precise, but the regression model classified more of the healthy class correctly. XGBoost was more accurate in identifying individuals who later suffered a myocardial infarction. Receiver operator characteristic (ROC) scores are class size invariant. In this metric XGBoost outperformed the logistic regression model, with ROC scores of 0.86 (accuracy 0.75 (CI ±0.00379) and 0.77 (accuracy 0.77 (CI ± 0.00369) respectively. Secondly, we demonstrate how SHAPley values can be used to visualize and interpret the predictions made by XGBoost models, both for the cohort test set and for individuals. The XGBoost machine learning model shows very promising results in evaluating risk of MI in a large and diverse population. This model can be used, and visualized, both for individual assessments and in larger cohorts. The predictions made by the XGBoost models, points toward a future where "Explainable AI" may help to bridge the gap between medicine and data science. [ABSTRACT FROM AUTHOR]

Background: It is commonly assumed that high oestradiol levels in women are cardioprotective. We assessed the association between oestradiol and the risk of incident myocardial infarction (MI) in women.Methods: We used data from 263 295 female UK Biobank participants [mean age 56.2; standard deviation (SD) 8.0 years] without previous cardiovascular disease (CVD). Associations of oestradiol with age and other cardiovascular risk factors were assessed. Cox proportional hazards models estimated crude, ag- and multiple-adjusted hazard ratios (HR) for MI associated with oestradiol levels.Results: After a mean follow-up of 9 years, 2206 incident cases of MI had been recorded, including 230 events among the 57 204 women (mean age 48) with detectable oestradiol levels. In the unadjusted analyses, a unit higher in log-transformed oestradiol was associated with an HR [95% confidence interval (CI) for MI of 0.73 (0.58; 0.92)]. After adjusting for age, this HR became 0.94 (0.75; 1.17), and after further adjusting for classical CVD risk factors, it was 1.05 (0.83; 1.31. Results were similar in subgroup analyses defined by age, menopausal status, socioeconomic status, contraceptive pill use and the use of hormone replacement therapy. The multivariable-adjusted HR for the 171 431 women (mean age 59) with undetectable levels of oestradiol, compared with those with detectable levels, was 0.97 (0.92; 1.02).Conclusions: Higher levels of oestradiol were not associated with a decreased risk of MI. The presumed cardioprotective effects of oestradiol seem to be largely confounded by age and further confounded by other cardiovascular risk factors. [ABSTRACT FROM AUTHOR]

Background: Alcohol consumption is a leading contributor to death and disability worldwide, but previous research has not examined the effects of different patterns of alcohol consumption. The study objective was to understand the relationship between different alcohol consumption patterns and adverse health outcomes risk, adjusting for average amount consumed among regular drinkers.Methods: This was a prospective cohort study of UK Biobank (UKB) participants. Abstainers, infrequent alcohol consumers or those with previous cancer, myocardial infarction (MI), stroke or liver cirrhosis were excluded. We used beverage type, consumption with food and consumption frequency as exposures and adjusted for potential confounding. All-cause mortality, major cardiovascular events-MACE (MI/stroke/cardiovascular death), accidents/injuries, liver cirrhosis, all-cause and alcohol-related cancer incidence over 9-year median follow-up period were outcomes of interest.Results: The final sample size for analysis was N = 309,123 (61.5% of UKB sample). Spirit drinking was associated with higher adjusted mortality (hazard ratio (HR) 1.25; 95% confidence intervals (CI) 1.14-1.38), MACE (HR 1.31; 95% CI 1.15-1.50), cirrhosis (HR 1.48; 95% CI 1.08-2.03) and accident/injuries (HR 1.10; 95% CI 1.03-1.19) risk compared to red wine drinking, after adjusting for the average weekly alcohol consumption amounts. Beer/cider drinkers were also at a higher risk of mortality (HR 1.18; 95% CI 1.10-1.27), MACE (HR 1.16; 95% CI 1.05-1.27), cirrhosis (HR 1.36; 95% CI 1.06-1.74) and accidents/injuries (HR 1.11; 95% CI 1.06-1.17). Alcohol consumption without food was associated with higher adjusted mortality (HR 1.10; 95% CI 1.02-1.17) risk, compared to consumption with food. Alcohol consumption over 1-2 times/week had higher adjusted mortality (HR 1.09; 95% CI 1.03-1.16) and MACE (HR 1.14; 95% CI 1.06-1.23) risk, compared to 3-4 times/week, adjusting for the amount of alcohol consumed.Conclusion: Red wine drinking, consumption with food and spreading alcohol intake over 3-4 days were associated with lower risk of mortality and vascular events among regular alcohol drinkers, after adjusting for the effects of average amount consumed. Selection bias and residual confounding are important possible limitations. These findings, if replicated and validated, have the potential to influence policy and practice advice on less harmful patterns of alcohol consumption. [ABSTRACT FROM AUTHOR]

The association between use of aromatase inhibitors (AIs) and cardiovascular outcomes is controversial. While some observational studies have assessed the cardiovascular safety of AIs as upfront treatments, their cardiotoxicity as sequential treatments with tamoxifen remains unknown. Thus, we conducted a population-based cohort study using data from the United Kingdom Clinical Practice Research Datalink linked to the Hospital Episode Statistics and Office for National Statistics databases. We employed a prevalent new-user design to propensity-score match, in a 1:2 ratio, patients switching from tamoxifen to AIs with patients continuing tamoxifen between 1998 and 2016. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals for the study outcomes (myocardial infarction, ischemic stroke, heart failure, and cardiovascular mortality). Overall, 1,962 patients switching to AIs were matched to 3,874 patients continuing tamoxifen. Compared with tamoxifen, AIs were associated with an increased risk of myocardial infarction (hazard ratio (HR) = 2.08, 95% confidence interval (CI): 1.02, 4.27). The hazard ratios were elevated for ischemic stroke (HR = 1.58, 95% CI: 0.85, 2.93) and heart failure (HR = 1.69, 95% CI: 0.79, 3.62) but not cardiovascular mortality (HR = 0.87, 95% CI: 0.49, 1.54), with confidence intervals including the null value. The elevated hazard ratios observed for the cardiovascular outcomes should be corroborated in future large observational studies. [ABSTRACT FROM AUTHOR]

Objective: Diabetes has shown to be a stronger risk factor for myocardial infarction (MI) in women than men. Whether sex differences exist across the glycemic spectrum is unknown. We investigated sex differences in the associations of diabetes status and glycated hemoglobin (HbA1c) with the risk of MI.Research Design and Methods: Data were used from 471,399 (56% women) individuals without cardiovascular disease (CVD) included in the UK Biobank. Sex-specific incidence rates were calculated by diabetes status and across levels of HbA1c using Poisson regression. Cox proportional hazards analyses estimated sex-specific hazard ratios (HRs) and women-to-men ratios by diabetes status and HbA1c for MI during a mean follow-up of 9 years.Results: Women had lower incidence rates of MI than men, regardless of diabetes status or HbA1c level. Compared with individuals without diabetes, prediabetes, undiagnosed diabetes, and previously diagnosed diabetes were associated with an increased risk of MI in both sexes. Previously diagnosed diabetes was more strongly associated with MI in women (HR 2.33 [95% CI 1.96; 2.78]) than men (1.81 [1.63; 2.02]), with a women-to-men ratio of HRs of 1.29 (1.05; 1.58). Each 1% higher HbA1c, independent of diabetes status, was associated with an 18% greater risk of MI in both women and men.Conclusions: Although the incidence of MI was higher in men than women, the presence of diabetes is associated with a greater excess relative risk of MI in women. However, each 1% higher HbA1c was associated with an 18% greater risk of MI in both women and men. [ABSTRACT FROM AUTHOR]

Background: Microvascular obstruction affects one-half of patients with ST-segment elevation myocardial infarction and confers an adverse prognosis.Objectives: This study aimed to determine whether the efficacy and safety of a therapeutic strategy involving low-dose intracoronary alteplase infused early after coronary reperfusion associates with ischemic time.Methods: This study was conducted in a prospective, multicenter, parallel group, 1:1:1 randomized, dose-ranging trial in patients undergoing primary percutaneous coronary intervention. Ischemic time, defined as the time from symptom onset to coronary reperfusion, was a pre-specified subgroup of interest. Between March 17, 2016, and December 21, 2017, 440 patients, presenting with ST-segment elevation myocardial infarction within 6 h of symptom onset (<2 h, n = 107; ≥2 h but <4 h, n = 235; ≥4 h to 6 h, n = 98), were enrolled at 11 U.K. hospitals. Participants were randomly assigned to treatment with placebo (n = 151), alteplase 10 mg (n = 144), or alteplase 20 mg (n = 145). The primary outcome was the amount of microvascular obstruction (MVO) (percentage of left ventricular mass) quantified by cardiac magnetic resonance imaging at 2 to 7 days (available for 396 of 440).Results: Overall, there was no association between alteplase dose and the extent of MVO (p for trend = 0.128). However, in patients with an ischemic time ≥4 to 6 h, alteplase increased the mean extent of MVO compared with placebo: 1.14% (placebo) versus 3.11% (10 mg) versus 5.20% (20 mg); p = 0.009 for the trend. The interaction between ischemic time and alteplase dose was statistically significant (p = 0.018).Conclusion: In patients presenting with ST-segment elevation myocardial infarction and an ischemic time ≥4 to 6 h, adjunctive treatment with low-dose intracoronary alteplase during primary percutaneous coronary intervention was associated with increased MVO. Intracoronary alteplase may be harmful for this subgroup. (A Trial of Low-Dose Adjunctive Alteplase During Primary PCI [T-TIME]; NCT02257294). [ABSTRACT FROM AUTHOR]

Background: Clonal hematopoiesis of indeterminate potential (CHIP) refers to clonal expansion of hematopoietic stem cells attributable to acquired leukemic mutations in genes such as DNMT3A or TET2. In humans, CHIP associates with prevalent myocardial infarction. In mice, CHIP accelerates atherosclerosis and increases IL-6/IL-1β expression, raising the hypothesis that IL-6 pathway antagonism in CHIP carriers would decrease cardiovascular disease (CVD) risk.Methods: We analyzed exome sequences from 35 416 individuals in the UK Biobank without prevalent CVD, to identify participants with DNMT3A or TET2 CHIP. We used the IL6R p.Asp358Ala coding mutation as a genetic proxy for IL-6 inhibition. We tested the association of CHIP status with incident CVD events (myocardial infarction, coronary revascularization, stroke, or death), and whether it was modified by IL6R p.Asp358Ala.Results: We identified 1079 (3.0%) individuals with CHIP, including 432 (1.2%) with large clones (allele fraction >10%). During 6.9-year median follow-up, CHIP associated with increased incident CVD event risk (hazard ratio, 1.27 [95% CI, 1.04-1.56], P=0.019), with greater risk from large CHIP clones (hazard ratio, 1.59 [95% CI, 1.21-2.09], P<0.001). IL6R p.Asp358Ala attenuated CVD event risk among participants with large CHIP clones (hazard ratio, 0.46 [95% CI, 0.29-0.73], P<0.001) but not in individuals without CHIP (hazard ratio, 0.95 [95% CI, 0.89-1.01], P=0.08; Pinteraction=0.003). In 9951 independent participants, the association of CHIP status with myocardial infarction similarly varied by IL6R p.Asp358Ala (Pinteraction=0.036).Conclusions: CHIP is associated with increased risk of incident CVD. Among carriers of large CHIP clones, genetically reduced IL-6 signaling abrogated this risk. [ABSTRACT FROM AUTHOR]

Background: Sociodemographic, health- and work-related factors have been found to influence return to work in cancer survivors. It is feasible though that behavioural factors, such as expectation of being at work, could also affect work-related outcomes. Therefore, the effect of earlier identified factors and expectation of being at work on future employment status in cancer survivors was explored. To assess the degree to which these factors specifically concern cancer survivors, a comparison with heart attack survivors was made.Methods: Data from the English Longitudinal Study of Ageing were used. Cancer and heart attack survivors of working age in the UK were included and followed up for 2 years. Baseline characteristics of both cancer and heart attack survivors were compared regarding employment status. Univariate and multivariate regression analyses were performed in survivors at work, and the interaction between independent variables and diagnose group was assessed.Results: In cancer survivors at work (N = 159), alcohol consumption, participating in moderate or vigorous sport activities, general health and participation were univariate associated with employment status at two-year follow-up. Only fair general health (compared to very good general health) remained statistically significant in the multivariate model (OR 0.31; 95% CI 0.13-0.76; p = 0.010). In heart attack survivors at work (N = 78), gender, general health and expectation of being at work were univariate associated with employment status at follow-up. Female gender (OR 0.03; 95% CI 0.00-0.57; p = 0.018) and high expectation of being at work (OR 10.68; 95% CI 1.23-93.92; p = 0.033) remained significant in the multivariate model. The influence of gender (p = 0.066) and general health (p = 0.020) regarding employment status was found to differ significantly between cancer and heart attack survivors.Conclusions: When predicting future employment status in cancer survivors in the UK, general health is the most relevant factor to consider. While expectation of being at work did not show any significant influence in cancer survivors, in heart attack survivors, it should not be disregarded though, when developing interventions to affect their employment status. Future research should focus on more specific measures for expectation, and additional behavioural factors, such as self-efficacy, and their effect on employment status. [ABSTRACT FROM AUTHOR]

Background Both the incidence of myocardial infarction (MI) and short-term case fatality have declined in the UK. However, little is known about trends in longer-term survival following an MI. The aim of the study was to investigate trends in longer-term survival, alongside trends in medication prescribing in primary care. Methods Data came from 218 general practices contributing to the Health Improvement Network, a UK-wide primary care database. 3-year survival and medication use were determined for 6586 men and 3766 women who had an MI between 1991 and 2002 and had already survived 3 months. Results Adjusting for age and gender, the 3-year post- MI case-fatality rate among 3-month survivors fell by 28% (95% CI 13 to 40), from 83 deaths per 1000 person-years for MI occurring in 1991-2 to 61 deaths per 1000 person-years for MI in 2001-2. Relative declines in the case-fatality rate of 37% (20 to 50) and 14% (-11 to 34) were observed for men and women, respectively (p=0.06 for interaction). Prescribing in the 3 months following the MI of lipid-regulating drugs increased from 3% of patients in 1991 to 79% in 2002, prescribing of beta-blockers increased from 26% to 68%, prescribing of ACE inhibitors increased from 11% to 71% and prescribing of anti-platelet medication increased from 46% to 86%. Conclusion There has been a moderate improvement in longer-term survival following an MI, distinct from improvements in short-term survival, although men may have benefited more than women. Increased medication prescribing in primary care may be a contributing factor. [ABSTRACT FROM AUTHOR]

Objective To compare ordinary least squares (OLS) and instrumental variable (IV) estimates of the effects of COX-2 selective inhibitor non-steroidal anti-inflammatory drugs (COX-2s) relative to non-selective NSAIDs (non-selectives) on incidence of gastrointestinal (GI) bleeding, and acute myocardial infarction (MI). We test the validity of the IV estimates, and compare to estimates from randomised controlled trials (RCTs). Design Cohort study using administration data. Setting Primary care. Participants 93 562 patients aged over 65 years attending one of 104 general practices (GP) in the UK. Main outcomes GI bleeding and acute MI. Methods We use data from the UK general practice research database. Our outcomes are incident gastrointestinal bleeding and myocardial infarctions within 60, 120, 180 and 360 days of the first prescription. We estimate risk differences in outcomes using OLS and IVs, using physician prior prescribing as an IV, and compare them to RCT estimates. Results The OLS estimates suggested COX-2s were positively associated with GI bleeds, and were negatively associated with MI. Adjusted OLS estimates were attenuated. In contrast our IV estimates imply –0.43(–1.54,0.68) fewer GI bleeds per 100 people treated with COX-2s after 180 days. The IV estimates provide little evidence, −0.55(−1.2, 1.5), of a difference in MI between treatments. These are comparable to previously published IV estimates and RCT evidence. Conclusions Deriving causal treatment effects using observational health data has proven to be problematic. We demonstrate that in contrast to IV based estimates, conventional OLS methods fail to estimate casual effects as indicated by RCTs. [ABSTRACT FROM PUBLISHER]

Background: Suppression of prostacyclin (PGI2) is implicated in the cardiovascular hazard from inhibitors of cyclooxygenase (COX)-2. Furthermore, estrogen confers atheroprotection via COX-2-dependent PGI2 in mice, raising the possibility that COX inhibitors may undermine the cardioprotection, suggested by observational studies, of endogenous or exogenous estrogens.Methods and Findings: To identify an interaction between hormone therapy (HT) and COX inhibition, we measured a priori the association between concomitant nonsteroidal anti-inflammatory drugs (NSAIDs), excluding aspirin, in peri- and postmenopausal women on HT and the incidence of myocardial infarction (MI) in a population-based epidemiological study. The odds ratio (OR) of MI in 1,673 individuals and 7,005 controls was increased from 0.66 (95% confidence interval [CI] 0.50-0.88) when taking HT in the absence of traditional (t)NSAIDs to 1.50 (95% CI 0.85-2.64) when taking the combination of HT and tNSAIDs, resulting in a significant (p < 0.002) interaction. The OR when taking aspirin at doses of 150 mg/d or more was 1.41 (95% CI 0.47-4.22). However, a similar interaction was not observed with other commonly used drugs, including lower doses of aspirin, which target preferentially COX-1.Conclusions: Whether estrogens confer cardioprotection remains controversial. Such a benefit was observed only in perimenopausal women in the only large randomized trial designed to address this issue. Should such a benefit exist, these results raise the possibility that COX inhibitors may undermine the cardioprotective effects of HT. [ABSTRACT FROM AUTHOR]